Bryk began by highlighting the genius of randomization. When we isolate one factor and ignore everything thing else we ignore the variability in outcomes that we observe.

We need evidence based practice and practice-based evidence.

He drew strongly on health systems improvement: If doctors can learn how to make complex organizations better through industrial car manufacture, education might be able to lean from the healthcare systems. Bryk has been a student of healthcare quality and improvement to see what can be learned to help system change in education, citing this TED talk:

We see the power of networks to address common problems, move rapidly and solve problems that were previously too complex. It challenges us normatively (if we usually think as individuals).

“We can accomplish more together than even the best of us can accomplish alone”

Managing complex problem-solving – 6 key areas to consider

1. Make work problem specific and user centred – use human centred design.

“See the problem through the lens of the person who is actually experiencing it” – what are their actual lived experiences?

2. Focus on variation in performance

– what factors are driving this variation? The question is not “what works?”, but “How to advance effectiveness among diverse practitioners, engaging varied populations of children and families and working across different contexts.”

3. See the system that produces current outcomes

– why do we continue to get the outcomes we have always got? In a design process, let’s go out and try and understand the problem from the teachers perspectives for a couple of weeks.

4. We cannot improve at scale what we cannot measure

– if you want to improve the issues that you can see, go back through the systems that are producing them. We must be specific about the qualitites we are wanting to measure. What specifically does quality look like?

5. Use disciplined inquiry to drive improvement

…we must be specific. What problems are we trying to solve? What are we doing to address it? How will I know it will make a difference? Can it be executed at scale? Do we have the capability? Do we have capacity? How will the people doing the work going to respond to it? If we can manage al these factors, then we can go large scale, but generally these are not the conditions for large scale reform. Try rapid, cycling prototyping. Variation in performance is the problem to solve.